We derive a set of analytical results for optimal income taxation with
tags using quasilinear preferences and a Rawlsian social welfare
function. Secondly, assuming a constant elasticity of labor supply
and log-normality of the skills distribution, we analytically identify
the winners and losers of tagging. Third, we prove that if the skills
distribution in one group first-order stochastically dominates the
other, tagging calls for redistribution from the former to the latter
group. Finally, we calibrate our model to the US workers using gender
as tag. Welfare implications are dramatic. Only male high-wage
earners lose. Everyone else gains, some substantially. (JEL H21,
H23, H24)